# io.github.cyanheads/imf-mcp-server > Query IMF SDMX 3.0 macroeconomic dataflows — WEO, BOP, CPI, exchange rates, 190 countries. - name: io.github.cyanheads/imf-mcp-server - version: 0.4.4 - connection class: R0 (autonomous) - trust: 94/100 - quality: 85/100 (good) - owner: not claimed - descriptor: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fimf-mcp-server - tools: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fimf-mcp-server/tools **An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe. ## Connection (mcpServers) ```json { "mcpServers": { "imf-mcp-server": { "type": "http", "url": "https://imf.caseyjhand.com/mcp" } } } ``` ## Trust - hygiene: 100 - liveness: 100 - freshness: 100 - provenance: 80 - drivers: +repository +namespace-matches-repo +reachable +uptime-100% +updated-4d-ago - Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. ## Quality 85/100 (good) ### protocol: 100 (weight 25) - pass `protocol.modern`: supports 2026-07-28 (server/discover) - pass `protocol.stateless`: answers without a session - pass `protocol.transport`: streamable HTTP - pass `protocol.list_ttl`: tool list is cacheable (ttlMs 3600000) ### authorization: n/a (weight 15) - n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth - n/a `auth.secret_in_url`: no templated URL ### tool hygiene: 79 (weight 30) - pass `tools.descriptions`: every tool has a description - warn `tools.description_length`: 2 tools have descriptions over 1,024 characters, which crowds the context - pass `tools.schemas`: every tool has an object input schema - pass `tools.annotations`: 5 of 5 tools declare readOnlyHint or destructiveHint - fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: imf_query_dataset (destructiveHint); imf_list_databases (destructiveHint); imf_get_database (destructiveHint); … - pass `tools.token_cost`: about 3,251 tokens to load every tool - pass `tools.api_dump`: tools are not a one-to-one API dump ### stability: 75 (weight 15) - warn `stability.changes`: 7 tool changes in 30 days - pass `stability.rug_pull`: no tool changed its meaning under the same name ### dependencies: n/a (weight 15) - n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: deps.dev does not know @cyanheads/imf-mcp-server@0.4.4, @cyanheads/imf-mcp-server@0.4.4 - tools: 5, about 3,251 tokens to load them all - tool set hash: ed41a2c30860ce23252fc7588c99ace1 - tools last changed: 2026-10-16T21:49:24.938Z - badge: [![protogrid quality](https://protogrid.dev/badge/io.github.cyanheads/imf-mcp-server.svg)](https://protogrid.dev/servers/io.github.cyanheads/imf-mcp-server) - Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. ### Tool changes - 2026-10-16 `imf_dataframe_query` changed (outputSchema) - 2026-10-16 `imf_query_dataset` changed (description, inputSchema, outputSchema) - before: Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries); * stands alone and cannot join a + list. Codes are matched case-insensitively and checked against each dimension's codelist before the query — an unknown code is rejected with the nearest valid codes. Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. last_n_observations keeps each series' last N observations — 1 is each series' latest value, the cheap way to ask many countries for their latest figure. Values are in base units everywhere, staged canvas rows included: scale is the power of ten the IMF publishes a series in (value / 10^scale is the published figure), never a factor still to apply. A response is held to 100,000 serialized characters. With DataCanvas enabled (CANVAS_PROVIDER_TYPE=duckdb), a larger result (multi-country, long time range) spills to it: call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis. Without DataCanvas, a larger result returns its earliest observations with truncated=true, and retrieval_guidance names the last period returned and how to narrow the query. - after: Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. An index series also carries the reference_period it is based on (e.g. 2010A, 2010=100) exactly as published, on the series and, where the dataflow publishes one per observation, on each observation. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries); * stands alone and cannot join a + list. Codes are matched case-insensitively and checked against each dimension's codelist before the query — an unknown code is rejected with the nearest valid codes. Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. When a + key returns data for some requested series and none for others, missing_series names each empty one with the reason a query for it alone gives (no_data or no_data_in_range). When the extra request that recovers the unit, scale, or decimals a + key suppresses fails, unresolved_attributes names them and how to get them. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. last_n_observations keeps each series' last N observations — 1 is each series' latest value, the cheap way to ask many countries for their latest figure. Values are in base units everywhere, staged canvas rows included: scale is the power of ten the IMF publishes a series in (value / 10^scale is the published figure), never a factor still to apply. A response is held to 100,000 serialized characters. With DataCanvas enabled (CANVAS_PROVIDER_TYPE=duckdb), a larger result (multi-country, long time range) spills to it: call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis. Without DataCanvas, a larger result returns its earliest observations with truncated=true, and retrieval_guidance names the last period returned and how to narrow the query. - 2026-10-16 `imf_get_database` changed (inputSchema, outputSchema) - 2026-10-16 `imf_list_databases` changed (description, inputSchema, outputSchema) - before: List IMF SDMX dataflows available on the portal. Entry point for every query: imf_get_database and imf_query_dataset both require a dataflow id obtained here. Vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE are excluded by default; set include_vintages=true to include them. Results are paged — 50 per call by default, adjustable with limit and offset — and total_count reports how many dataflows matched. Descriptions are shortened here; imf_get_database returns the full text for a single dataflow. - after: List IMF SDMX dataflows available on the portal. Entry point for every query: imf_get_database and imf_query_dataset both require a dataflow id obtained here. Vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE are excluded by default; set include_vintages=true to include them. Results are paged — 50 per call by default and at most 200, adjustable with limit and offset — and total_count reports how many dataflows matched. Descriptions are shortened here; imf_get_database returns the full text for a single dataflow. - 2026-09-30 `imf_query_dataset` changed (description, inputSchema, outputSchema) - before: Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries). Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. Large analytical result sets (multi-country, long time range) spill to DataCanvas; call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis. - after: Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries); * stands alone and cannot join a + list. Codes are matched case-insensitively and checked against each dimension's codelist before the query — an unknown code is rejected with the nearest valid codes. Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. last_n_observations keeps each series' last N observations — 1 is each series' latest value, the cheap way to ask many countries for their latest figure. Values are in base units everywhere, staged canvas rows included: scale is the power of ten the IMF publishes a series in (value / 10^scale is the published figure), never a factor still to apply. A response is held to 100,000 serialized characters. With DataCanvas enabled (CANVAS_PROVIDER_TYPE=duckdb), a larger result (multi-country, long time range) spills to it: call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis. Without DataCanvas, a larger result returns its earliest observations with truncated=true, and retrieval_guidance names the last period returned and how to narrow the query. - 2026-09-30 `imf_get_database` changed (description, inputSchema) - before: Fetch a dataflow's dimension list with a codelist preview for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "Constant prices" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Each codelist is capped at the first 50 entries by default, including previews filtered by codelist_filter. Set dimension_id to retrieve one codelist with bounded limit/offset paging after the optional substring filter. Set available_only=true to page codes the dataflow actually publishes, with series and time coverage metadata; availability filtering happens before codelist_filter and paging. The imf://database/{dataflow_id} resource provides the same bounded discovery summary. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow. - after: Fetch a dataflow's dimension list with a codelist preview for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "Constant prices" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Each codelist is capped at the first 50 entries by default, including previews filtered by codelist_filter. Set dimension_id to retrieve one codelist with bounded limit/offset paging after the optional codelist_filter, which keeps codes whose ID or name contains every word given. Set available_only=true to page codes the dataflow actually publishes, with series and time coverage metadata; availability filtering happens before codelist_filter and paging. The imf://database/{dataflow_id} resource provides the same bounded discovery summary. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow. - 2026-09-30 `imf_list_databases` changed (inputSchema) Full history: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fimf-mcp-server/changes ## Dependencies - npm @cyanheads/imf-mcp-server@0.4.4: unknown - npm @cyanheads/imf-mcp-server@0.4.4: unknown Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0. ## Remotes - https://imf.caseyjhand.com/mcp (streamable-http, auth none, reachable true, uptime30d 1) ## Packages - npm @cyanheads/imf-mcp-server@0.4.4 - npm @cyanheads/imf-mcp-server@0.4.4 ## Tools (5) - `imf_dataframe_describe`: List DataCanvas tables and columns staged by a prior imf_query_dataset call. Returns each table's name, row count, and column schema (name + DuckDB type). Required before imf_dataframe_query to discover the table and column names for SQL. - `imf_dataframe_query`: Run a read-only SQL SELECT against a DataCanvas table staged by imf_query_dataset. Supports multi-country comparisons, time-series aggregation, and cross-indicator joins. Requires imf_dataframe_describe first to discover table and column names. One SELECT statement per call; a leading WITH … SELECT (CTE) is accepted. DML and DDL are rejected. - `imf_get_database`: Fetch a dataflow's dimension list with a codelist preview for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "Constant prices" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Each codelist is capped at the first 50 entries by default, including previews filtered by codelist_filter. Set dimension_id to retrieve one codelist with bounded limit/offset paging after the optional codelist_filter, which keeps codes whose ID or name contains every word given. Set available_only=true to page codes the dataflow actually publishes, with series and time coverage metadata; availability filtering happens before codelist_filter and paging. The imf://database/{dataflow_id} resource provides the same bounded discovery summary. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow. - `imf_list_databases`: List IMF SDMX dataflows available on the portal. Entry point for every query: imf_get_database and imf_query_dataset both require a dataflow id obtained here. Vintage (historical snapshot) dataflows such as WEO_2025_OCT_VINTAGE are excluded by default; set include_vintages=true to include them. Results are paged — 50 per call by default and at most 200, adjustable with limit and offset — and total_count reports how many dataflows matched. Descriptions are shortened here; imf_get_database returns the full text for a single dataflow. - `imf_query_dataset`: Query an IMF SDMX dataflow by dimension key over a time range. Returns observations with time_period, value, and status, plus the unit, scale, and decimals of each series — a key resolving to several series carries one entry per series in series_metadata, since unit and scale differ between them. An index series also carries the reference_period it is based on (e.g. 2010A, 2010=100) exactly as published, on the series and, where the dataflow publishes one per observation, on each observation. Requires imf_get_database first to obtain the correct key_format and valid dimension codes. Country codes are ISO 3-letter (USA, GBR, DEU — not US, GB, DE). Key format: dot-separated codes in DSD keyPosition order (e.g. USA.NGDP_RPCH.A for WEO). Every position must carry a code: use + to combine codes (e.g. USA+GBR.NGDP_RPCH.A) and * to match every code at a position (e.g. *.NGDP_RPCH.A for all countries); * stands alone and cannot join a + list. Codes are matched case-insensitively and checked against each dimension's codelist before the query — an unknown code is rejected with the nearest valid codes. Codelists from imf_get_database enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series. When a + key returns data for some requested series and none for others, missing_series names each empty one with the reason a query for it alone gives (no_data or no_data_in_range). When the extra request that recovers the unit, scale, or decimals a + key suppresses fails, unresolved_attributes names them and how to get them. start_period and end_period must be valid period strings (YYYY, YYYY-SN, YYYY-QN, YYYY-MM, or a calendar-valid YYYY-MM-DD) with start_period no later than end_period; malformed or reversed ranges are rejected. A bound covers the whole period it names, so end_period 2023 includes 2023-M12 and 2023-Q4. last_n_observations keeps each series' last N observations — 1 is each series' latest value, the cheap way to ask many countries for their latest figure. Values are in base units everywhere, staged canvas rows included: scale is the power of ten the IMF publishes a series in (value / 10^scale is the published figure), never a factor still to apply. A response is held to 100,000 serialized characters. With DataCanvas enabled (CANVAS_PROVIDER_TYPE=duckdb), a larger result (multi-country, long time range) spills to it: call imf_dataframe_describe first to inspect staged tables and columns, then imf_dataframe_query for SQL analysis. Without DataCanvas, a larger result returns its earliest observations with truncated=true, and retrieval_guidance names the last period returned and how to narrow the query.